RagMetrics
Monitor your LLM calls. Test your LLM app.
RagMetrics offers:
- The best LLM judge on the market (>95% human agreement)
- A/B testing for your entire LLM pipeline
- Evaluations for retrievals, not just generation
With this package, you can log your LLM calls to RagMetrics and use them as labeled data
Quickstart
pip install ragmetrics-client
import ragmetrics
from openai import OpenAI
## login to ragmetrics account via portal key
ragmetrics.login(key="your_ragmetrics_key")
openai_client = OpenAI()
## Monitor OpenAI, LangChain or LiteLLM clients
ragmetrics.monitor(openai_client)
## Then use as usual. All calls will be logged
resp = openai_client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": f"What is the capital of Spain?"}]
)
Get your key and read docs at RagMetrics.ai
1 maintainer
Metadata
1 maintainer
Release files for ragmetrics-client 0.2.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ragmetrics_client-0.2.1.tar.gz | 35.0 kB | Without provenance | Details for ragmetrics_client-0.2.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| ragmetrics_client-0.2.1-py3-none-any.whl | Python 3 | none | any | Details for ragmetrics_client-0.2.1-py3-none-any.whl |
Total release size: 71.8 kB
Release files / ragmetrics_client-0.2.1.tar.gz
| Download URL | ragmetrics_client-0.2.1.tar.gz |
|---|---|
| Size | 35.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / ragmetrics_client-0.2.1-py3-none-any.whl
| Download URL | ragmetrics_client-0.2.1-py3-none-any.whl |
|---|---|
| Size | 36.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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